Bright-field microscope panoramic image alignment algorithm based on total variation region selection

A panoramic image and total variation technology, applied in the field of image processing, can solve problems such as a large amount of tasks, and achieve the effect of overcoming high computational complexity

Active Publication Date: 2021-09-07
易普森智慧健康科技(深圳)有限公司
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  • Description
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Problems solved by technology

[0011] (4) It is necessary to achieve stitching and alignment of panoramic images of thousands of megapixel images, which requires a large amount of tasks

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  • Bright-field microscope panoramic image alignment algorithm based on total variation region selection
  • Bright-field microscope panoramic image alignment algorithm based on total variation region selection
  • Bright-field microscope panoramic image alignment algorithm based on total variation region selection

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Embodiment Construction

[0063] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0064] combine Figure 1-Figure 3 The present invention is described in detail

[0065] The present invention provides a bright field microscope panoramic image alignment algorithm based on total variation region selection, comprising the following steps:

[0066] S1, input a number of images to be spliced ​​(aligned), more than 2 in number;

[0067] S2, extracting prior overlapping regions;

[0068] S3, the second total score extracts the feature area;

[0069] S4, using the MSE mean square error to calculate the relative offset;

[0070] S5, calculating the global offset of the image;

[0071] S6, stitching the results of the panoramic images, and performing image cropping and translation according to the offset data calculated in step S5 to complete the stitching.

[0072] The specific method is as follows:

[0073] (1) Based on the a...

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Abstract

The invention provides a bright-field microscope panoramic image alignment algorithm based on total variation region selection. The bright-field microscope panoramic image alignment algorithm comprises the following steps of inputting a plurality of images to be spliced, extracting a priori overlapping region, extracting a feature region through secondary total variation, calculating relative offset by adopting an MSE mean square error, calculating image global offset, and splicing a panoramic image result. Area selection is carried out by adopting a mode based on secondary total variation, an area which is rich in content and strong in image edge information is found out to serve as an alignment template, then pixel information is utilized to match an optimal position through MSE measurement, offset between adjacent images is determined in combination with a bilateral total variation weighting mode, and the purpose of two-direction alignment is achieved. Priori knowledge is obtained for the overlapping amount of two adjacent view images, so that the defect of high calculation complexity of an alignment mode based on pixels is overcome.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a bright-field microscope panoramic image alignment algorithm based on total variation region selection. Background technique [0002] Image registration algorithms are mainly divided into two categories: pixel-based registration algorithms and feature-based registration algorithms. [0003] Registration algorithms based on pixel information can be roughly divided into three categories: cross-correlation method (also called template matching method), sequential similarity detection and matching method, and mutual information method. Among them, the registration method based on mutual information is more flexible and more accurate than other registration methods based on global information content, and has become one of the most popular image registration methods. Frederik Maes and Andre Collignon applied mutual information to measure the statistical dependence or inform...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/181G06T7/60G06T7/70G06T5/50
CPCG06T7/181G06T7/60G06T7/70G06T5/50G06T2207/10056
Inventor 李小军高崇军
Owner 易普森智慧健康科技(深圳)有限公司
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